Stochastic Resonance-Based Multi-Node Cooperative Sensing Algorithm

Dual-threshold energy detection algorithm is a relatively common spectrum sensing algorithm, but its detection performance is poor and the results are not accurate enough in low signal-to-noise ratio conditions. This article proposes a dual-threshold energy detection algorithm based on stochastic resonance. The value of the double threshold is first determined based on the uncertainty factor, and then the perceived information is subjected to hard and soft judgments. In performing the soft judgement, a multi-node cooperative perception model based on random resonance operator is constructed, and the improved manta ray algorithm is used to find the perception model weight ration to achieve effective perception of the signal. Simulation results show that the algorithm has a clear improvement in sensing effectiveness compared with other sensing algorithms at low signal-to-noise ratios.